Automating facial emotion recognition

Issue title: Emotional Machines: The Next Revolution

Guest editors: Valentina Franzoni, Alfredo Milani, Daniele Nardi and Jordi Vallverdú

Article type: Research Article

Authors: Gervasi, Osvaldo^a | Franzoni, Valentina^{b; *} | Riganelli, Matteo^c | Tasso, Sergio^a

Affiliations: [a] Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1 – 06123 Perugia, Italy. E-mails: osvaldo.gervasi@unipg.it, sergio.tasso@unipg.it | [b] Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Via Ariosto, 20, Rome, Italy. E-mail: valentina.franzoni@dmi.unipg.it | [c] Voc. Listricciano, 217, 06055 Papiano (PG), Italy. E-mail: matteoriganelli@gmail.com

Correspondence: [*] Corresponding author. E-mail: valentina.franzoni@dmi.unipg.it.

Abstract: The work described in this paper attempts to contribute to one of the most stimulating and promising sectors in the field of emotion recognition, which is health care. Multidisciplinary studies in artificial intelligence, augmented reality, and psychology stressed out the importance of emotions in communication and awareness. The intent is the recognition of human emotions, processing images streamed in real-time from a mobile device. The proposed techniques involve the use of open source libraries of visual recognition and machine learning approaches based on convolutional neural networks (CNN).

Keywords: Image recognition, emotion recognition, face detection, machine learning, convolutional neural networks

DOI: 10.3233/WEB-190397

Journal: Web Intelligence, vol. 17, no. 1, pp. 17-27, 2019